Dynamical downscaling is one of the major approaches to obtain finer-scale weather and climate information. Dynamical downscaling has a broad application prospect and needs in meteorology, hydrology, agriculture, ecosystem, wind power, and atmospheric environment studies and projections.

The severe and sustained droughts in Southwest China (SWC) during the last decade results in tremendous losses including crop failure, lack of drinking water, ecosystem destruction, health problem and even deaths (Figure 1). Devastating droughts in SWC have attracted great concerns from both the Chinese government and the science community.

Changes in extreme climate events could have notable impacts on human mortality, regional economies, and natural ecosystems and therefore such events are of great public concern and interest. However, to understand and predict regional scale or even local scale climate extremes is a great challenge not only because they are rare but also because they are sometime, if not often, non-Gaussian distribution.

Under the background of global warming and climate extremes increasing, an increasing demand of high quality daily climatic observations is needed in climate change studies. Meanwhile, homogenized climatic series are becoming more and more important.